KR20110027574A - Pattern characteristic-detection apparatus for photomask and pattern characteristic-detection method for ph0tomask - Google Patents

Abstract

PURPOSE: A pattern characteristic detecting apparatus of a photo mask and a pattern characteristic detecting method of a photo mask are provided to find property distribution on the entire area of a photo mask before light exposure, thereby controlling a light exposure condition of a light exposure process according to property distribution. CONSTITUTION: A detection data writing unit(2) writes detection data based on an optical image of a pattern formed on a photo mask. A reference data writing unit(3) writes reference data of the pattern. An extraction unit(5) extracts a pattern for detecting a pattern property from the reference data. The first area setting unit sets an area where a pattern property is detected based on the detected pattern. A detection unit(4) detects a pattern property of a target pattern for detecting a pattern property in a pattern property detecting area.

Description

PATTERN CHARACTERISTIC-DETECTION APPARATUS FOR PHOTOMASK AND PATTERN CHARACTERISTIC-DETECTION METHOD FOR PH0TOMASK}

Embodiments disclosed herein generally relate to an apparatus for detecting characteristics of a photomask and a method for detecting characteristics of a photomask.

BACKGROUND ART In the fields of semiconductor devices, flat panel displays, micro electro mechanical systems (MEMS), circuit boards, optical devices, mechanical devices, and the like, various structures having patterns formed on their surfaces have been manufactured. In the production of such spherical bodies, various kinds of inspections are performed to find out whether there are any defects such as abnormalities in the pattern shape, abnormalities in the pattern dimension, and the presence of foreign matter.

As a method of finding a defect of a pattern formed on the surface of a structure, an inspection method called a die-to-database method is known. According to this inspection method, a defect is detected by comparing inspection data with reference data. In order to obtain inspection data, an enlarged optical image of a pattern is formed on a light receiving surface such as a charge coupled device (CCD) image sensor. On the other hand, reference data is obtained based on design data (CAD data) used for designing a pattern. If a difference exists between the inspection data and the reference data, the difference is detected as a defect.

The known pattern inspection apparatus detects a defect such as an inappropriate size and an inappropriate position of a contact hole pattern, which is a fine pattern, based on the sum of the luminance values of the light passing through the inspection subject region (for example, Japanese Patent Laid-Open Publication No. 7-128248 (1995).

The photomask inspection apparatus used to manufacture the semiconductor device checks whether there are any defects and also sometimes detects the line width of fine line-and-space patterns.

 In addition, an apparatus for evaluating the transferability of a photomask pattern to be transferred to the surface of a wafer by an exposure apparatus is known. This apparatus captures an enlarged optical image of the pattern of the photomask with a CCD sensor or the like using an optical system equivalent to that of the exposure apparatus to detect the transmittance or line width of the obtained wafer surface pattern.

However, a device capable of evaluating transferability includes transmittance of a contact hole pattern; And a technique with limited ability to detect the line width of the line and space pattern. In particular, this technique can only perform detection within a limited area. That is, the apparatus can perform detection at predetermined intervals, but cannot detect with high resolution over the entire area of the photomask. On the other hand, some of the devices for inspecting the photomasks have a function for obtaining the distribution of the line width, but still could not obtain the line width distribution in consideration of the transferability. Therefore, the characteristics or characteristic distribution (transmittance distribution, line width distribution considering transferability, etc.) of the photomask could not be detected with high resolution over the entire area of the photomask.

Patterns in photomasks have become more and more refined in recent years. In such a situation, there is an increasing demand for improving the detection sensitivity of the contact hole pattern and accurately evaluating the quality of the photomask, the deterioration factor of the process margin due to the photomask, and the like.

However, the conventional technique of detecting the transmittance or the line width could not detect the characteristic or characteristic distribution of the photomask. Thus, for example, if the process margin or yield is lowered due to an abnormality which is not serious enough to be regarded as a defect, the cause of the degradation cannot be identified.

In general, according to one embodiment, the pattern characteristic detection apparatus of the photomask includes a detection data creation unit, a reference data creation unit, an extraction unit, a first area setting unit, a detection unit, and an aggregation unit. The said detection data preparation part is comprised so that detection data may be created based on the optical image of the pattern formed on the photomask. The reference data creation unit is configured to create reference data of the pattern. The extraction unit is configured to extract a pattern characteristic detection pattern from the reference data and to extract positional information of the extracted pattern. The first area setting unit is configured to set an area to detect a pattern characteristic based on the extracted pattern, and to extract a target pattern for pattern characteristic detection from the detection data based on the position information of the extracted pattern. The detection unit is configured to detect the pattern characteristics of the target pattern for pattern characteristic detection in the region where the pattern characteristics are to be detected by converting the light intensity of the optical image formed on the CCD image sensor into an electric digital signal. The aggregation unit is also configured to aggregate the detected pattern characteristics.

According to still another embodiment, the pattern characteristic detection apparatus of the photomask includes a detection data generation unit, a reference data generation unit, an extraction unit, an inverse transformation unit, a wafer surface pattern calculation unit, a second region setting unit, a detection unit, and an aggregation unit. The detection data creation unit is configured to create detection data based on the optical image of the pattern formed on the photomask. The reference data creation unit is configured to create reference data of the pattern. The extraction unit is configured to extract a pattern characteristic detection pattern from the reference data and to extract positional information of the extracted pattern. The inverse transform unit is configured to perform an inverse transform process to obtain a pattern formed on the photomask from the detection data. The wafer surface pattern calculator is configured to obtain a wafer surface pattern from the pattern formed on the photomask. The second region setting unit is configured to set an area to detect the pattern characteristic based on the extracted pattern, and is configured to extract a target pattern for pattern characteristic detection from the wafer surface pattern based on position information of the extracted pattern. do. The detection unit is configured to detect the pattern characteristic of the target pattern for pattern characteristic detection in the region where the pattern characteristic is to be detected. The aggregation unit is also configured to aggregate the detected pattern characteristics.

According to still another embodiment, the pattern characteristic detection apparatus of the photomask includes a detection data generation unit, a reference data generation unit, an extraction unit, a conversion unit, a wafer surface pattern calculation unit, a second region setting unit, a detection unit, and an aggregation unit. The detection data creation unit is configured to create detection data based on the optical image of the pattern formed on the photo mask. The reference data creation unit is configured to create reference data of the pattern. The extraction unit is configured to extract a pattern characteristic detection pattern from the reference data and to extract positional information of the extracted pattern. The conversion unit is configured to obtain a pattern formed on the photomask from the detection data by obtaining a pattern most correlated with the detection data by a correlation operation. The wafer surface pattern calculator is configured to obtain a wafer surface pattern from the pattern formed on the photomask. The second area setting unit is configured to set an area to detect the pattern characteristic based on the extracted pattern, and extract a target pattern for pattern characteristic detection from the wafer surface pattern based on position information of the extracted pattern. The detection unit is configured to detect the pattern characteristic of the target pattern for pattern characteristic detection in the region where the pattern characteristic is to be detected. The aggregation unit is configured to aggregate the detected pattern characteristics.

According to yet another embodiment, a method of detecting pattern characteristics of a photomask is disclosed. The method includes creating detection data based on an optical image of a pattern formed on the photomask and creating reference data of the pattern. The method includes extracting a pattern characteristic detection pattern from the reference data and extracting position information of the extracted pattern. The method includes setting an area to detect a pattern characteristic based on the extracted pattern, and extracting a target pattern for pattern characteristic detection from the detection data based on the position information of the extracted pattern. The method includes detecting a pattern characteristic of the target pattern for pattern characteristic detection target in a region where the pattern characteristic is to be detected. The method also includes aggregating the detected pattern characteristics.

According to still another embodiment, a method of detecting pattern characteristics of a photomask is disclosed. The method includes creating detection data based on an optical image of a pattern formed on the photomask and creating reference data of the pattern. The method includes extracting a pattern characteristic detection pattern from the reference data and extracting position information of the extracted pattern. The method includes performing an inverse transform process to obtain a pattern formed on the photomask from the detection data. The method includes obtaining a wafer surface pattern from a pattern formed on the photomask. The method includes setting a region to detect pattern characteristics based on the extracted pattern, and extracting the characteristic detection target pattern from the wafer surface pattern based on position information of the extracted pattern. The method includes detecting a pattern characteristic of the characteristic detection target pattern in a region where the pattern characteristic is to be detected. The method also includes aggregating the detected pattern characteristics.

According to the invention, it is possible to detect the characteristics and distribution of characteristics of the photomask with high resolution over the entire area of the photomask by the pattern characteristic detection apparatus of the photomask and the pattern characteristic detection method of the photomask.

1 is a block diagram for illustrating a characteristic detection apparatus of a photomask according to this embodiment.
2 is a schematic diagram for illustrating an extraction unit.
3 is a block diagram for illustrating a variable template.
4 is a block diagram for illustrating a method of performing feature detection and feature aggregation.
5 is a block diagram illustrating a case where a variable template is provided.
6 is a block diagram for illustrating the inverse conversion process and the calculation of the wafer surface pattern.
7 is a block diagram for illustrating a conversion unit.

Hereinafter, some embodiments will be described with reference to the drawings. In the following drawings, the same or similar reference numerals represent the same or similar components, and detailed description thereof will be omitted as appropriate.

1 is a block diagram for illustrating a characteristic detection apparatus of a photomask according to this embodiment.

1 shows a characteristic detection apparatus 1 including a detection data preparation unit 2, a reference data preparation unit 2, a characteristic detection unit 4, an extraction unit 5, and a display unit 6.

The detection data preparation unit 2 includes a light source 21, an illumination optical system 22, a mounting unit 23, an imaging optical system 24, a detection unit 25, and a conversion unit 26.

The detection data preparation unit 2 creates detection data based on the optical image of the pattern formed in the test sample 100 (for example, a photomask).

The light source 21 emits the detection light 21a. As the light source 21, various kinds of light sources, for example, light sources emitting white light, monochromatic light, coherent light, and the like can be used. The light source used as the light source for detecting the fine pattern is preferably a light source capable of emitting the short detection wavelength 21a. One example of such a light source is a YAG laser light source that emits detection light 21a having a wavelength of 266 nm. Note that the light source 21 is not limited to the laser light source. Other kinds of light sources may be appropriately selected for the size of the pattern or other determinants.

The illumination optical system 22 guides the detection light 21a exiting the light source 21. The detection light 21a guided in this way is illuminated on the detection area of the test sample 100. The illumination optical system 22 also controls the size of the portion irradiated by the detection light 21a.

The imaging optical system 24 guides the detection light 21a from the test sample 100. The detection light 21a guided in this way is reflected on the light receiving surface of the detector 25 to form an image on the light receiving surface.

Each of the illumination optical system 22 and the imaging optical system 24 has the same structure as that shown in FIG. 1. The configuration includes various optical elements such as lenses. The type and position of the optical element shown in FIG. 1 is not limited to those illustrated only and may be appropriately changed. Each of the illumination optical system 22 and the imaging optical system 24 may include optical elements other than those shown in FIG. 1 as needed. Some of the additional optical elements that are acceptable are mirrors, apertures, beam splitters, magnification changers and zoom mechanisms.

The imaging optical system 24 shown in FIG. 1 guides the detection part 25 to the detection light 21a which permeate | transmitted the test sample 100. FIG. However, the imaging optical system 24 may be configured to guide the detection unit 25 with the detection light 21a reflected by the test sample 100.

The mounting part 23 holds the test sample 100 mounted on the mounting part 23. Since the mounting unit 23 is provided with an unillustrated unit for moving the test sample 100 mounted on the mounting unit 23 from one position to another position, the position to be actually detected can be appropriately changed. An unshown unit for moving the test sample 100 does not necessarily need to be provided in the mounting unit 23. All that is needed is a unit for changing the relative position to be actually detected. An acceptable solution is to provide an unshown unit for moving and changing the position of the illumination optical system 22, the imaging optical system 24, the detector 25, and the like.

 The detection part 25 converts the light of the optical image formed on the light receiving surface into electricity. For example, a charge coupled device (CCD) sensor, a CCD line sensor, a time delay and integration (TDI) sensor, or the like may be used as the detection unit 25. However, the detector 25 is not limited to these sensors. A sensor capable of converting the light of the formed optical image into electricity may be appropriately selected.

The converter 26 converts the analog electric signal output from the detector 25 into a digital signal. Thereafter, the converter 26 graphically analyzes the resultant digital electric signal to create detection data.

The reference data creating unit 3 includes a data storing unit 31, a data developing unit 32, and a data creating unit 33.

The reference data creating unit 3 creates reference data based on design data and the like stored in the data storage unit 31. The reference data created in this way by the reference data creating unit 3 is for a pattern formed in the photomask.

The data storage unit 31 stores such data, such as drawing data used to form a pattern or design data before being converted into drawing data.

The data developing unit 32 develops two-dimensional data by developing design data and the like obtained from the data storage unit 31.

The data creating unit 33 creates reference data by graphically analyzing the resultant two-dimensional data. The reference data is created to suit the resolution of the detection data. In particular, the data generating unit 33 converts the data developed by the data developing unit 32 to a high resolution, such as the resolution of the optical image data (that is, the detection data) obtained by the detection unit 25. do.

The extraction unit 5 extracts from the reference data a pattern that is the same as the shape and size of the target pattern for detecting the characteristic (for example, transmittance, etc.). The extraction unit 5 outputs a signal (ie, a valid flag) related to the extracted pattern (ie, a reference pattern) to the area setting unit 43. When outputting the above-described signal, the extraction unit 5 also outputs position information of the extracted pattern (ie, the reference pattern), that is, information on where the extracted pattern (ie, the reference pattern) is located in the photomask. .

In summary, the extractor 5 extracts both the reference pattern corresponding to the target pattern for characteristic detection and the positional information (reference pattern) of the extracted pattern from the reference data. Thereafter, the extraction unit 5 outputs both the signal (effective flag) for the extracted reference pattern and the positional information of the reference pattern to the area setting unit 43. The extraction part 5 is demonstrated in more detail later.

The characteristic detector 4 includes a first characteristic detector 4a and a second characteristic detector 4b. A plurality of characteristic detectors may be provided, each of which is provided with a first characteristic detector 4a and a second characteristic detector 4b.

The first characteristic detection unit 4a detects the characteristics (eg, transmittance, etc.) of the pattern of the detection data corresponding to the reference pattern extracted by the extraction unit 5. In addition, the first characteristic detection unit 4a performs an aggregation process or the like on the characteristic thus detected.

The 1st characteristic detection part 4a contains the area | region setting part 43, the detection part 44a, and the aggregation part 45a.

Based on the signal (that is, the valid flag) received from the extraction unit 5, the area setting unit 43 sets an area as a target area in which the characteristics (for example, transmittance, etc.) of the pattern are detected. Further, based on the positional information received from the extraction section 5, the area setting section 43 extracts a target pattern for characteristic detection from the detection data. In other words, based on the reference data, the area setting unit 43 determines the area in which the characteristic is to be detected. Also based on the positional information, the area extraction unit 43 extracts a target pattern for characteristic detection from the detection data.

The detection part 44a detects the characteristic of a pattern based on the area | region set as the target area | region for characteristic detection by the area | region setting part 43, and the target pattern for characteristic detection. That is, the detection part 44a detects the characteristic of the target pattern for the characteristic detection located in the target area | region for the characteristic detection.

The aggregation unit 45a aggregates the characteristics detected by the detection unit 44a. The aggregation unit 45a may be configured to aggregate characteristics of the entire area of the photomask based on the detected characteristics. In addition, the counting unit 45a may be configured to generate information on a characteristic distribution (for example, transmittance distribution, etc.) based on the detected characteristic and positional information.

The second characteristic detection unit 4b performs an inverse transform process to obtain a pattern formed in the photomask from the detection data. Next, based on the pattern formed in the photomask, the second characteristic detection unit 4b obtains a pattern (wafer surface pattern) to be transferred to the surface of the test sample 100 by simulation. Thereafter, the second characteristic detection unit 4b detects the characteristics (eg, transmittance, etc.) of the wafer surface pattern corresponding to the specific position of the reference pattern, and performs an aggregation process or the like on the detected characteristics. Details of the inverse conversion process and the calculation using the wafer surface pattern will be described later.

The second characteristic detection unit 4b includes an inverse conversion unit 41, a wafer surface pattern calculation unit 42, an area setting unit 43, a detection unit 44b, and an aggregation unit 45b.

The inverse transform unit 41 performs an inverse transform process to obtain a pattern formed in the photomask from the detection data. The inverse conversion process measures the optical imaging characteristics of the imaging optical system 24, that is, the point spread function (PSF) of the imaging optical system 24 and the sensitivity distribution of the pixels included in the detection unit 25. Use the phase-forming function shown.

The wafer surface calculating section 42 is obtained by the inverse converting section 41, and obtains a wafer surface pattern from the pattern formed on the photomask.

Based on the signal (ie, valid flag) received from the extraction unit 5, the area setting unit 43 sets an area as an area in which the characteristics (for example, transmittance, etc.) of the pattern are detected. Further, based on the positional information received from the extraction section 5, the area setting section 43 extracts the target pattern for the characteristic detection from the wafer surface pattern obtained by the wafer surface pattern calculating section 42. That is, based on the reference pattern, the area setting unit 43 determines the area in which the characteristic is to be detected. In addition, based on the positional information, the area setting unit 43 extracts a target pattern for characteristic detection from the wafer surface pattern.

The detection part 44b detects the characteristic of a pattern based on the characteristic detection area | region set as the target area | region by the area | region setting part 43, and the target pattern for characteristic detection. That is, the detection unit 44b detects the characteristic of the target pattern for characteristic detection located in the target region for characteristic detection.

The aggregation unit 45b aggregates the characteristics detected by the detection unit 44b. The aggregation unit 45b may be configured to aggregate characteristics of the entire area of the photomask based on the detected characteristics. In addition, the counting unit 45b may be configured to generate information about a characteristic distribution (for example, transmittance distribution, etc.) based on the detected characteristic and positional information.

The method of determining the target area for characteristic detection, the method of performing the characteristic detection, and the method of performing the aggregation processing of the characteristic will be described in more detail later.

The display unit 6 provides a visual representation based on the data of the characteristics aggregated by the aggregation units 45a and 45b. For example, the display unit 6 may display a characteristic distribution chart (for example, transmittance distribution chart). As described above, the aggregation sections 45a and 45b can create information on the characteristic distribution, but the display section 6 can create such information instead of the aggregation sections 45a and 45b. The display unit 6 may switch to display the type (eg, shape, size, etc.) of the pattern to be displayed from one to the other. In addition, the display unit 6 can switch the characteristic to be displayed from the characteristics detected by the first characteristic detector 4a to the characteristic detected by the second characteristic detector 4b or vice versa. In addition, the display unit 6 can appropriately set the area to be displayed, the distribution intensity, and the like.

The display portion 6 does not necessarily need to be provided to the characteristic detection device 1, but may be appropriately provided. For example, the storage unit (not shown) may be provided in the characteristic detection device 1 in place of the display unit 6. The storage unit stores, in particular, data of characteristics aggregated by the aggregation units 45a and 45b.

Next, the extraction part 5 is further demonstrated.

2A to 2G are schematic diagrams for showing the extraction part. 2A is a block diagram for illustrating an extraction unit. 2B-2D are schematic diagrams for illustrating a method of performing template matching. 2E is a schematic diagram showing a position where a pattern dimension is detected. 2F is a schematic diagram for illustrating a method of detecting pattern dimensions. 2G is a schematic diagram illustrating a method of performing matching based on the area of a pattern.

As shown in FIG. 2A, the extraction unit 5 includes a first matching unit 35, a second matching unit 36, and an AND operation unit 39.

In this embodiment, the second matching section 36 performs a pattern matching operation on the pattern selected by the first matching section 35. Therefore, the target pattern can be extracted with higher precision.

The first matching unit 35 selects from the reference data a pattern that is the same as the shape and size of the target pattern for the characteristic detection. The selection is made by performing the template matching process shown in Figs. 2B to 2D. In particular, the pattern 101 shown in FIG. 2B can be selected by performing the template matching process shown in FIG. 2D, using the template shown in FIG. 2C and having thresholds 102 and 103. The threshold value 102 is used when the target area for matching has a light emission amount smaller than the predetermined amount. The threshold 103 is used when the target area for matching has a light emission amount larger than a predetermined amount. The template shown in FIG. 2C is a fixed template in which the target area where the matching is performed by the threshold value 102 is located around the target area where the matching is performed by the threshold value 103.

The second matching unit 36 includes a pattern dimension calculating unit 37 and a pattern area calculating unit 38.

The pattern dimension calculating section 37 performs a pattern matching process by calculating the dimension of the pattern. For example, as shown in FIG. 2E, the pattern dimension calculating unit 37 performs a pattern matching process by calculating pattern dimensions in directions perpendicular to each other. In this case, as shown in FIG. 2F, each of the pattern dimensions may be calculated based on the profile 104 of the light emission amount and the predetermined threshold value 105. For example, the dimension of the profile 104 at the threshold 105 (indicated by the reference numeral 105 in FIG. 2F) can be defined as the dimension of the pattern.

The pattern area calculating part 38 performs a pattern matching process by calculating the area of a pattern. For example, as shown in FIG. 2G, the pattern area calculating unit 38 performs a pattern matching process by calculating an area within the predetermined area 106 and a light transmittance larger than a predetermined threshold value. The aforementioned area 106 is shown in FIG. 2C and is assumed to be an area equivalent to the target area for matching performed with the threshold 102.

The AND product 39 performs an AND operation on the matching result output from the pattern dimension calculating unit 37 and the pattern area calculating unit 38. In this way, the pattern extracted from the reference data is a reference pattern having the same shape and size as that of the target pattern for characteristic detection.

Although the template shown in FIG. 2C is a fixed template, instead of the fixed template, a variable template capable of arbitrarily setting a matching area may be used if necessary. The extraction unit 5 may be provided with a variable template which can arbitrarily set the logic used in each of the pixels included in the template as necessary.

3 is a block diagram for illustrating a variable template. In more detail, the block diagram of FIG. 3 illustrates the variable template 50 included in the first matching unit 35. As shown in FIG. 3, the variable template 50 includes a delay unit 51, a buffering unit 52, a binarization unit 53, a matching unit 54, and an AND operation unit 57.

The delay unit 51 delays the transmission of the electrical signal of the reference data by a certain length of time without changing the waveform of the electrical signal of the reference data. The buffering unit 52 receives reference data input to the buffering unit 52 through the delay unit 51. Accumulate as data of N x N pixels.

The binarization section 53 includes conversion sections 53a and 53b. The converters 53a and 53b perform binarization using different threshold values with respect to each other. Some examples of thresholds are threshold 102 and threshold 103.

The data of N x N pixels stored in the buffering unit 52 are binarized by the binarization unit 25 using different threshold values, and the binarized data respectively correspond to different groups of N x N pixels. It comprises a pixel matching unit (54 ₀ to 54 _N-1). Note that the threshold can be changed as needed.

Matching unit 54 includes a pixel matching unit (54 ₀ to 54 _N-1) each corresponding to the N x N pixels in the other group. Each pixel matching unit (54 ₀ to 54 _N-1) includes a logic operation unit (55a and 55b) and a logical product operation unit (56).

The logic used by each of the logic calculators 55a and 55b can be set as needed. By setting the logic of the logic calculating sections 55a and 55b as necessary, the template is formed as a variable template, where the logic used for each pixel of the template can be set as needed.

For example, in the logic operation unit 55a, the following three logics, that is, 'value of a specific pixel> threshold 103'; 'value of a specific pixel ≤ threshold 103; And 'operation not required' are selected and set. On the other hand, in the logic calculating section 55b, the following three logics, that is, 'value of a specific pixel> threshold 102'; 'Value of the specific pixel ≤ threshold 102'; And 'operation not required' are selected and set. The determination by the logic set in this way is performed on the data provided by the binarization unit 53.

The aforementioned option 'operation not required' may be selected and set when the value of a specific pixel is apparent. For example, the pixel located in the portion corresponding to the hole of the hole pattern (ie, the light transmitting portion) is clearly in the 'bright' state. In this case, by selecting and setting the value '1' shown in Fig. 3, it can be determined that the pixel is always 'ON' (bright).

The AND product 56 performs an AND operation on the determination result output from the logic operators 55a and 55b. Accordingly, the AND product 56 outputs a matching result for the specific pixel.

The AND product 57 again performs an AND operation on the matching result performed by the logic operation unit 56 in each of the pixel matching units 54 ₀ to 54 _N-1 . When matching is completed, the AND product 57 outputs a 'template matching result'. The template matching result is output to the area setting unit 43 as a valid flag.

Therefore, according to the logical setting of the template, the logical product of the matching result of all N x N pixels can be calculated. Thus, template matching can be performed with logic set as needed. When template matching is performed with logic set as needed, a template more suitable for the shape of the target pattern for the characteristic detection and the like can be easily set based on the 'detection recipe' or the like.

Next, the aggregation performed on the detection of the characteristics (for example, transmittance, etc.) and the characteristics will be described in detail.

4 is a block diagram illustrating a method of performing feature detection and aggregation of features. 4 shows an example of performing detection of the transmittance and aggregation of the transmittance.

As shown in FIG. 4, based on the signal (effective flag) received from the extraction part 5, the area | region setting part 43 sets the area | region as a target area | region where the transmittance | permeability of a pattern is detected. Here, based on the signal (effective flag) received from the extraction section 5, the area setting section 43 selects a template more suitable for the shape of the target pattern for the transmittance detection. Further, based on the positional information received from the extraction section 5, the area setting section 43 extracts a target pattern for the transmittance detection from the detection data.

The detection unit 44a detects the transmittance of the pattern based on the area set by the area setting unit 43 and the target pattern for transmissivity detection. For example, the detection part 44a detects the transmittance of a pattern by calculating the total of the data of the part which has a value larger than a predetermined threshold value in a set area | region.

The aggregation part 45a aggregates the transmittance | permeability detected by the detection part 44a. The aggregation unit 45a may be configured to aggregate the transmittance of the entire area of the photomask. In addition, the counting unit 45a may be configured to generate information on the transmittance distribution based on the detected transmittance and position information.

Note that the description given by referring to FIG. 4 is based on the case of the first characteristic detection section 4a. In the case of the second characteristic detection section 4b, the detection of the transmittance and the aggregation of the detected transmittance can be performed in a similar manner.

In the case described so far, the fixed template is installed in the area setting unit 43, but the variable template may be installed in the area setting unit 43.

5 is a block diagram illustrating a case where a variable template is provided.

5 shows a third characteristic detection unit 4c including a buffering unit 60, a variable template 61, an arithmetic unit 63, an AND product 64, and an aggregation unit 65.

The buffering section 61 accumulates the input detection data as data of N x N pixels.

The variable template 61 includes a selector 62. The selector 62 includes pixel selectors 62a ₀ to 62a _N-1 , each corresponding to a different group of N × N pixels. In each of the pixel selection units 62a ₀ to 62a _N-1 , it is possible to set whether or not data of a specific pixel is selected (selection of pixels). By selecting a certain pixel from the pixels included in the detected data, the selector 62 can set a specific area as an area in which the characteristic is detected. Then, the calculating part 63 calculates the total of the detection data in the set area.

The detection data is input to the pixel selection units 62a ₀ to 62a _N-1 corresponding to NxN pixels of different groups, respectively, through the buffering unit 60 that stores data of N × N pixels. The pixel selection units 62a ₀ to 62a _N-1 are configured to operate according to the setting of whether or not a specific pixel is selected. Accordingly, the calculator 63 may calculate the sum of the values of certain pixels set as described above. In this way, if necessary, the pixel can be selected as the pixel set for the detection data and the sum of the values of the selected pixels can be calculated.

The logical product unit 64 calculates the logical product of the total value of the detection data calculated by the operation unit 63 and the valid flag received from the extraction unit 5. In this way, the sum (characteristic value) in the target pattern for characteristic detection corresponding to the reference pattern can be calculated.

Therefore, the sum (characteristic value) of all N x N pixels can be calculated according to the logic setting of the variable template 61. Therefore, characteristic detection can be performed with logic set as needed. If the characteristic detection can be performed with logic set as necessary, a template more suitable for the shape of the target pattern for the characteristic detection and the like can be easily set based on the 'detection recipe' or the like.

Next, the reverse conversion operation and the calculation of the wafer surface pattern will be described.

6 is a block diagram for illustrating the inverse transform operation and the calculation of the wafer surface pattern.

As shown in FIG. 6, the inverse transform unit 41 includes an inverse Fourier transform unit 41a and an inverse transform calculator 41b.

The inverse Fourier transform unit 41a converts the detection data into inverse Fourier transform and converts the detection data into detection data on the Fourier plane.

The inverse transform calculator 41b calculates a pattern formed on the photomask from the detected data on the Fourier plane. For this purpose, the inverse transform calculating section 41b uses the optical imaging characteristic of the imaging optical system 24 and the image forming function of the detection section 25 in consideration of the point spread function (PSF).

The point distribution function (optical imaging characteristic) of the optical system and the image forming function of the detector 25 may be theoretically derived based on the optical characteristics or the characteristics of the detector 25 (for example, the so-called center characteristic). . Alternatively, the optical imaging properties and the imaging function may be determined by experiment or other methods.

The method of obtaining the pattern formed in the photomask from the detection data is demonstrated in detail.

According to the theory of image formation, the output of the detection part 25 is represented by following formula (1). The output of the detector 25 first performs a convolution operation using the point distribution function (optical imaging characteristic) of the optical system and the image forming function of the detector 25, that is, the sensitivity distribution of each pixel of the detector 25. Obtained by performing. Following the convolution operation, sampling is performed using a comb function comb corresponding to the discrete sampling of the detection unit 25.

    i (x) = [d (x) * psf (x) * o (x)] comb (x) (1)

In equation (1), i (x) is the output (detection data) of the detector 25, d (x) is the image forming function (function of the sensitivity distribution of the sensor pixel) of the detector 25, and psf (x ) Is the point distribution (optical imaging characteristic) of the optical system, o (x) is the optical image obtained by the detection unit 25, comb (x) is a function indicating the pixel position (array) of the pitch p, Represents a convolution operation.

By Fourier transforming equation (1), equation (2) is obtained.

    I (u) = D (u) OTF (u) O (u) * comb (u) ... (2)

In Equation (2), I (u) is Fourier transformed from the output (detection data) from the detector 25, and D (u) is the image forming function (sensitivity distribution of the sensor pixel) of the detector 25. Function) is a Fourier transform, OTF (u) is a Fourier transform of the point distribution function (optical imaging characteristic) of the optical system, and O (u) is a Fourier transform of the optical image obtained by the detection unit 25. , comb (u) is a Fourier transform of a function indicating a pixel position (array) of pitch p, and * denotes a convolution operation.

Then, equation (3) is obtained by inverse Fourier transform of equation (2). In this way, the pattern formed in the photomask on the Fourier surface can be obtained from the output signal of the detector 25.

     O (u) * comb (u) = I (u) / D (u) OTF (u) ... (3)

In the Fourier transform such as the transform performed as described above, the bandwidth is limited by the pixel pitch p of the detector 25. In this case, by performing zero padding when Fourier transforming the output (detected data) from the detector 25, the band in the Fourier plane can be widened.

Next, the wafer surface pattern calculating part 42 is demonstrated again with reference to FIG.

The wafer surface pattern calculating section 42 includes a regular Fourier transforming section 42a and an image forming calculating section 42b.

The imaging operation part 42b obtains a wafer surface pattern based on the pattern (namely, the pattern formed in the photomask) calculated by the inverse conversion operation part 41b. In particular, the wafer surface pattern on the Fourier surface is obtained by transfer simulation. In the simulation, the light source intensity distribution of the exposure apparatus, the copper function of the optical system, the aberration characteristics of the optical system, etc. are taken into account. Transcription simulations can be performed using known optical simulation tools and computational hardware for lithography. Therefore, the transfer simulation is not described.

The regular Fourier transforming unit 42a performs Fourier transform on the wafer surface pattern on the Fourier surface to obtain a pattern (wafer surface pattern in the actual space) transferred to the surface of the test sample 100.

Next, operation | movement of the characteristic detection apparatus 1 of a photomask, and the characteristic detection method of a photomask are demonstrated. First, the conveying apparatus or operator which is not shown arrange | positions the test sample 100 to the mounting part 3.

 Thereafter, the light source 21 emits the detection light 21a. The detection light 21a emitted from the light source 21 is guided by the illumination optical system 22 to the detection area of the inspection sample 100, and the illumination optical system 22 is a portion irradiated by the detection light 21a. Control the size of the. Thereafter, the relative position at which the characteristic test is actually performed in the test sample 100 mounted on the mounting unit 23 is changed using a unit not shown which moves the test sample 100 and the like.

The detection light 21a from the test sample 100 is guided on the light receiving surface of the detection unit 25 by the imaging optical system 24 to form an image on the light receiving surface. Light of the optical image formed on the light receiving surface is converted into electricity by the detection unit 25. Thereafter, the electrical signal obtained by the photoelectric conversion performed by the detection unit 25 is converted into a digital signal by the conversion unit 26. Thereafter, the converter 26 graphically analyzes the resultant digital electric signal to create detection data.

As the detection of the inspection sample 100 proceeds, the data storage unit 31 of the reference data creating unit 3 supplies design data and the like to the data developing unit 32, where the supplied data is developed into two-dimensional data. do. The resulting two-dimensional data is graphically analyzed by the data creating unit 33 to create reference data. Thereafter, the extraction unit 5 extracts a pattern (that is, a reference pattern) having the same shape and size as that of the target pattern for characteristic detection from the reference data. The extraction unit 5 outputs a signal (ie, a valid flag) for the extracted pattern to the area setting unit 43. When outputting the above-described signal, the extraction unit 5 also outputs position information of the extracted pattern, that is, information on where the pattern extracted from the photomask is located. Extraction of the reference pattern may be performed using a fixed template, a variable template, or the like.

Thereafter, the characteristic detector 4 detects the characteristic of the target pattern for detection, and performs an aggregation process or the like on the characteristic thus detected. Based on the signal (that is, the valid flag) received from the extraction unit 5, the area setting unit 43 sets an area as a target area for detecting the characteristic of the pattern. Further, based on the positional information received from the extraction section 5, the area setting section 43 extracts a target pattern for characteristic detection from the detection data.

In particular, based on the detection data, the first characteristic detection unit 4a detects the characteristic of the target pattern for detection, and performs an aggregation process or the like on the detected characteristic. In addition, the second characteristic detection unit 4b obtains the wafer surface pattern from the detection data. Based on the wafer surface pattern thus obtained, the second characteristic detection unit 4b detects the characteristic of the target pattern for detection, and performs an aggregation process or the like on the detected characteristic. The data of the characteristic on which the aggregation process and the like have been performed is visualized by the display unit 6. In addition, the display unit 6 may display the characteristic distribution over the entire area of the photomask.

The method for detecting characteristics of the photomask according to the embodiment is performed in the following manner. Based on the optical image of the pattern formed in the test sample 100, detection data is created. The reference data of the pattern formed in the test sample 100 is created. The reference pattern corresponding to the target pattern for the feature detection and the positional information of the reference pattern are extracted from the reference data. A region where the characteristic is detected is set based on the reference pattern, and a target pattern for characteristic detection is extracted from the detection data based on the positional information. The characteristic of the target pattern for the characteristic detection in the target area for the characteristic detection is detected. Aggregate detected features.

Alternatively, detection data is generated based on the optical image of the pattern formed on the test sample 100. The reference data of the pattern formed in the test sample 100 is created. Both the reference pattern corresponding to the target pattern for characteristic detection and the positional information of the reference pattern are extracted from the reference data. The pattern formed on the photomask is obtained from the detection data by performing inverse transform processing. The wafer surface pattern is obtained from the pattern formed on the photomask. The region where the characteristic is detected is set based on the reference pattern, and the target pattern for characteristic detection is extracted from the wafer surface pattern based on the positional information. The characteristic of the target pattern for the characteristic detection in the target area for the characteristic detection is detected. The detected characteristic is aggregated.

Moreover, based on the detected characteristic and positional information, the information about the characteristic distribution can be created.

If necessary, a reference pattern may be extracted using a variable template that may set logic used for pixels included in the template. It is also possible to set the logic based on the 'detection recipe'.

In the above description, the characteristics of the photomask are transmittance, but other kinds of characteristics may be used. For example, the line width based on the line width measurement can be measured in a manner similar to that in the case of transmittance measurement. It is also possible to detect the transmittance in the region of the critical position. Moreover, the information regarding the characteristic distribution of these other characteristics can also be created. Thus, the user may have an idea of the property distribution of other properties over the entire area of the photomask. Some of the features may be combined as needed. The combined characteristics can then be detected or aggregated. For example, the transmittance and the line width on the wafer surface may be detected from the wafer surface pattern. Thereafter, it may be obtained by counting the transmittance distribution and the line width distribution over the entire area of the photomask. In addition, the detection of the characteristics of the photomask can be combined by inspection of the photomask or the like. For example, a transmittance distribution such as a hole pattern that is particularly noticed while the defect of the photomask is checked may be obtained for the entire area of the photomask. Thus, the user can recognize that there are abnormalities that are not important to be identified as defects. Therefore, the user can accurately evaluate the quality of the photomask, the deterioration factor of the process margin due to the photomask, and the like.

According to this embodiment, the characteristic (for example, transmittance, line width, etc.) and the characteristic distribution (for example, transmittance distribution, line width distribution, etc.) can be detected with respect to the whole area | region of a photomask. If an abnormality exists that is not serious enough to be regarded as a defect, this abnormality may lower the process margin or yield. Even when these problems occur, the cause of the problems can be identified accurately.

For example, photomask quality can be evaluated in terms of uniformity or variation in transmittance or linewidth. In addition, process margins associated with photomasks can be evaluated. Thus, the yield of the lithography process can be improved.

In addition, setting of a template, setting of parameters of a pattern to be extracted (for example, parameters for forming and size of a pattern), setting of an area where a transmittance or line width is detected, or another type of setting may be applied to a 'detection recipe' or the like. May be appropriately performed. In summary, a template used for extracting a pattern or the like may be set as needed based on a "detection recipe" or the like.

Next, another embodiment of the present invention will be described. This embodiment can be applied when the pattern formed in the photomask is obtained from the detection data.

7 is a block diagram for illustrating a conversion unit.

7 illustrates a transform unit 141 including a shape change unit 142, a convolution calculator 143, a correlation calculator 144, and an optimizer 145.

The shape changing unit 142 changes the shape and size of the pattern by changing the line width value and / or resizing the parameter in a stepwise manner.

The convolution calculator 143 performs a convolution operation using a point distribution function (optical imaging characteristic) of the optical system and an image forming function representing the sensitivity distribution of the pixels included in the detector 25.

The correlation operation unit 144 performs a correlation operation between the pattern data and the detection data obtained by the convolution operation.

The optimizer 145 performs an optimization operation on the line width value and / or the resizing parameter based on the result of the correlation operation.

In the inverse transform unit 41 shown in Fig. 6, the detection data is transformed on the Fourier plane by inverse Fourier transform. From the detection data transformed on the Fourier surface, the pattern formed on the photomask is obtained using the optical imaging characteristic and the image forming function. According to this embodiment, on the other hand, the pattern having the highest correlation with the detection data is obtained by the correlation operation, and the pattern thus obtained is identified as a pattern formed in the photomask.

For example, the shape and size of the pattern in the design pattern input to the shape converting unit 142 are each changed by a predetermined value. Since the convolution operator 143 performs a convolution operation on the resulting pattern, the pattern formed on the photomask is obtained. Thereafter, a correlation operation is performed between the obtained pattern and the detection data. When the correlation is low, the optimizer 145 performs optimization to increase the correlation by performing optimization. Thereafter, the shape change unit 142 changes the line width and size of the pattern based on the optimization data. Thereafter, a series of operations are repeated to identify the pattern most correlated with the detection data as the pattern formed in the photomask.

According to this embodiment, even when it is difficult to perform inverse Fourier transform, the pattern formed on the photomask can be obtained from the detection data. Therefore, even when it is difficult to perform an inverse Fourier transform, the characteristics relating to the wafer surface pattern can be detected.

In addition, the contact hole pattern and the specific line and space pattern, as well as the transmittance of the critical position and the region of the critical position in the pattern design where the pattern is more likely to have defects, can be measured and displayed in a similar manner.

Next, the manufacturing method of the photomask which concerns on this embodiment is demonstrated.

According to the manufacturing method of the photomask which concerns on this embodiment, the characteristic detection apparatus 1 of a photomask, and the characteristic detection method of a photomask are characterized by the characteristic distribution (for example, transmittance distribution and line width distribution) with respect to the whole area | region of a photomask. Etc.). The result of the characteristic detection is taken to change the layout (exposure pattern data) of the pattern. A photomask is produced based on the changed pattern layout (exposure pattern data). In this case, the photomask can be manufactured by etching.

Alternatively, instead of changing the pattern layout (exposure pattern data), control information regarding the exposure conditions may be created. For example, control information can also be created so that exposure conditions can be changed according to the characteristic distribution.

According to the manufacturing method of the photomask which concerns on this embodiment, the photomask which has a uniform characteristic distribution with respect to the whole area | region of a photomask can be obtained. In addition, the user can recognize an abnormality that is not serious enough to be regarded as a defect. Therefore, the quality of the photomask can be improved. In addition, the template used for pattern extraction etc. can be set as needed based on a "detection recipe." Therefore, for example, the improvement in productivity, quality, and yield of a photomask can also be achieved. Further, if the control information of the exposure conditions can be prepared in order to change the exposure conditions in accordance with the characteristic distribution, the yield of the photomask can be improved. In addition, it is possible to achieve improvement in product quality and yield.

Next, the manufacturing method of the electronic device which concerns on this embodiment is demonstrated.

In the following description, the manufacturing method of a semiconductor device is demonstrated, for example.

The manufacturing method of a semiconductor device is performed by repeating a some process. One of a plurality of processes is a process of forming a pattern on a wafer by film formation, resist coating, exposure, development, etching, resist removal, and the like. Some of the other processes included in the plurality of processes described above are an inspection process, a cleaning process, a heat treatment process, an impurity introduction process, a diffusion process, and a planarization process. In the manufacture of a semiconductor device according to the above method, a photomask having uniform characteristics is produced by the above-described method for producing a photomask, and exposure is performed using the photomask thus prepared. In addition, since the user can know the characteristic distribution of the entire area of the photomask before the exposure, the user can control the exposure conditions in the exposure process according to the characteristic distribution. Here, the control can be performed based on "control information for changing exposure conditions in accordance with the characteristic distribution".

In processes other than the process using the manufacturing method of the photomask mentioned above, the technique of each well-known process can be used. Therefore, such other processes are not described.

The manufacturing method of the semiconductor device mentioned above is an example of the manufacturing method of the electronic device which concerns on this embodiment. However, the manufacturing method of the semiconductor future is not limited to this method. The manufacturing method of the electronic device of this embodiment can be widely used for manufacturing an electronic device using photolithography technology. For example, the method can be used for pattern formation (for example, pattern formation in liquid crystal color filters, array substrates, etc.) in the manufacture of flat panel displays.

According to the manufacturing method of the electronic device which concerns on this embodiment, a circuit pattern etc. are formed using the photomask which has a uniform characteristic. In addition, since the user can know the characteristic distribution of the entire area of the photomask before the exposure, the user can control the exposure conditions of the exposure process according to the characteristic distribution. When the circuit pattern and the like are deformed, various problems occur such as deterioration of electrical characteristics, bridging of the circuit pattern, and breaking of the circuit pattern. By controlling the exposure conditions according to the property distribution, these problems are prevented from occurring. Thus, the yield and quality of the product can be improved.

While some embodiments have been described so far, the present invention is not limited to these embodiments.

Where those skilled in the art appropriately modify the above-described embodiments, as long as such modified embodiments have the characteristic aspect of the present invention, the modified embodiments are still included within the scope of the present invention.

For example, the shape, dimensions, arrangement, number, and the like of each element included in the property detecting device 1 are not limited to those of each element in the description given so far, and may be changed as necessary.

In addition, the elements included in the above-described embodiments may be combined with each other as much as possible. Such combined examples are still included within the scope of the present invention as long as the specific aspects are included herein.

While specific embodiments have been described, these embodiments are provided by way of example only and are not intended to limit the scope of the invention. Indeed, the novel apparatus and methods described herein may be embodied in many different forms and furthermore, various omissions, substitutions, and exchanges of forms of the apparatuses and methods described herein may be made without departing from the spirit of the invention. have. The accompanying claims and their equivalents are intended to cover such forms or modifications as would fall within the scope and spirit of the inventions.

Claims (20)

A detection data generation unit configured to generate detection data based on an optical image of a pattern formed on the photomask;
A reference data creating unit configured to create reference data of the pattern;
An extraction unit configured to extract a pattern characteristic detection pattern from the reference data, and extract position information of the extracted pattern;
A first region setting unit configured to set a region to detect pattern characteristics based on the extracted pattern, and to extract a target pattern for pattern characteristic detection based on position information of the extracted pattern from the detection data;
A detector configured to detect the pattern characteristic of the target pattern for pattern characteristic detection in a region where the pattern characteristic is to be detected by converting the light intensity of the optical image formed on the CCD image sensor into an electric digital signal; And
The pattern characteristic detection apparatus of the photomask provided with the aggregation part comprised so that the detected pattern characteristic may be aggregated. The apparatus of claim 1, wherein the extractor comprises a variable matching template capable of setting any matching logic as needed based on a signal level of each pixel included in the template. The apparatus of claim 1, wherein the aggregation unit creates information on a pattern characteristic distribution based on the detected pattern characteristic and the positional information. The apparatus of claim 1, wherein the pattern characteristic is one or more kinds of characteristics selected from the group consisting of transmittance, line width, and transmittance in a region of a dangerous position. A detection data generation unit configured to create detection data based on an optical image of a pattern formed on the photomask;
A reference data creating unit configured to create reference data of the pattern;
An extraction unit configured to extract a pattern characteristic detection pattern from the reference data, and extract position information of the extracted pattern;
An inverse transform unit configured to perform an inverse transform process to obtain a pattern formed on the photomask from the detection data;
A wafer surface pattern calculator configured to obtain a wafer surface pattern from the pattern formed on the photomask;
A second region setting configured to set a region to detect pattern characteristics based on the extracted pattern, and configured to extract a target pattern for pattern characteristic detection based on position information of the extracted pattern from the wafer surface pattern part;
A detector configured to detect a pattern characteristic of the target pattern for pattern characteristic detection in a region in which the pattern characteristic is to be detected; And
The pattern characteristic detection apparatus of the photomask provided with the aggregation part comprised so that the detected pattern characteristic may be aggregated. The method of claim 5, wherein the detection data creation unit,
A light source configured to emit detection light;
An illumination optical system configured to guide detection light emitted from the light source to a photomask;
An imaging optical system configured to cause detection light from the photomask to form an optical image on the CCD image sensor of the detection section; And
A detection unit configured to convert light of an optical image formed on the CCD image sensor into an electric digital signal,
And the inverse conversion process is performed using both an optical imaging characteristic of the imaging optical system and an image-forming function representing the sensitivity distribution of pixels of the CCD image sensor of the detection unit. The apparatus of claim 5, wherein the extractor comprises a variable matching template capable of setting any matching logic as needed based on a signal level of each pixel included in the template. The apparatus of claim 5, wherein the aggregation unit creates information on a characteristic distribution based on the detected pattern characteristic and the positional information. The apparatus of claim 5, wherein the pattern characteristic is one or more kinds of characteristics selected from the group consisting of transmittance, line width, and transmittance in a region of a dangerous position. A detection data generation unit configured to create detection data based on an optical image of a pattern formed on the photo mask;
A reference data creating unit configured to create reference data of the pattern;
An extraction unit configured to extract a pattern characteristic detection pattern from the reference data, and extract position information of the extracted pattern;
A conversion unit configured to obtain a pattern formed on the photomask from the detection data by obtaining a pattern most correlated with the detection data by a correlation operation;
A wafer surface pattern calculator configured to obtain a wafer surface pattern from the pattern formed on the photomask;
A second region setting unit configured to set a region to detect pattern characteristics based on the extracted pattern, and extract a target pattern for pattern characteristic detection from the wafer surface pattern based on position information of the extracted pattern;
A detector configured to detect a pattern characteristic of the target pattern for pattern characteristic detection in a region in which the pattern characteristic is to be detected; And
The pattern characteristic detection apparatus of the photomask provided with the aggregation part comprised so that the detected pattern characteristic may be aggregated. The method of claim 10, wherein the detection data creation unit,
A light source configured to emit detection light;
An illumination optical system configured to guide detection light emitted from the light source to a photomask;
An imaging optical system configured to cause detection light from the photomask to form an image on a CCD image sensor of a detection unit; And
A detector configured to convert the light intensity of the optical image formed on the CCD image sensor into an electric digital signal,
The conversion unit,
A shape changer configured to change the pattern in a stepwise manner;
A convolution operator configured to perform a convolution operation on the changed pattern;
A correlation calculation unit configured to perform a correlation operation between data of the pattern resulting from the convolution operation and the detection data; And
An optimization unit configured to perform optimization based on a result of the correlation operation,
And the convolution operation is performed using both an optical imaging characteristic of the imaging optical system and an image forming function representing a sensitivity distribution of pixels of the CCD image sensor of the detection unit. The apparatus of claim 10, wherein the extractor comprises a variable matching template capable of setting any matching logic as necessary based on a signal level of each pixel included in the template. The apparatus of claim 10, wherein the aggregation unit creates information on a characteristic distribution based on the detected pattern characteristic and the positional information. The apparatus of claim 10, wherein the pattern characteristic is one or more kinds of characteristics selected from the group consisting of transmittance, line width, and transmittance in a region of a dangerous position. Creating detection data based on an optical image of a pattern formed on the photomask;
Creating reference data of the pattern;
Extracting a pattern characteristic detection pattern from the reference data and extracting position information of the extracted pattern;
Setting a region to detect pattern characteristics based on the extracted pattern, and extracting a target pattern for pattern characteristic detection from the detection data based on position information of the extracted pattern;
Detecting a pattern characteristic of the target characteristic pattern detecting pattern in a region in which the pattern characteristic is to be detected; And
A method for detecting pattern characteristics of a photomask, comprising the step of counting the detected pattern characteristics. 16. The method according to claim 15, further comprising the step of creating information relating to a characteristic distribution based on the detected pattern characteristic and the positional information. The method of claim 15, wherein the extraction of the reference pattern is performed using a variable template that can set any logic of pixels included in the template as needed.
And the logic is set based on the detection recipe. Creating detection data based on an optical image of a pattern formed on the photomask;
Creating reference data of the pattern;
Extracting a pattern characteristic detection pattern from the reference data and extracting position information of the extracted pattern;
Performing an inverse transform process to obtain a pattern formed on the photomask from the detection data;
Obtaining a wafer surface pattern from the pattern formed on the photomask;
Setting a region to detect pattern characteristics based on the extracted pattern, and extracting a target pattern for characteristic detection from the wafer surface pattern based on position information of the extracted pattern;
Detecting pattern characteristics of the characteristic detection target pattern in a region in which the pattern characteristics are to be detected; And
A method for detecting pattern characteristics of a photomask, comprising the step of counting the detected pattern characteristics. 19. The method according to claim 18, further comprising the step of creating information on a characteristic distribution based on said detected pattern characteristic and said positional information. The method of claim 18, wherein the extraction of the reference pattern is performed using a variable template that can set any logic of pixels included in the template as needed.
And the logic is set based on the detection recipe.

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